A locally-built, LLM-digested index of recent arXiv papers in quant finance, geometry/topology, and statistical ML — keyword search served straight from SQLite on this machine.
Efficiently optimizes orthogonal and Stiefel matrices on parallel units.
One reflection suffices for orthogonal weights, reducing GPU usage.
The ability to decompose a signal in an orthonormal basis (a set of orthogonal components, each normalized to have unit length) using a fast numerical procedure rests at the heart of many signal processing methods and applications. The classic examples are the Fourier and wavelet transforms that enjoy numerically effic…
A new algorithm speeds up matrix operations in Neural Networks.
HD algorithm simulates dynamics on random matrix ensembles without generating full matrices.
Dictionary learning is the task of determining a data-dependent transform that yields a sparse representation of some observed data. The dictionary learning problem is non-convex, and usually solved via computationally complex iterative algorithms. Furthermore, the resulting transforms obtained generally lack structure…
Study on Spanish households' investment choices in housing, deposits, and stocks.
Credit expansion led to stronger household leverage cycles during the U.S. business cycle.
Investment herding can reduce household consumption, a phenomenon called crowding-out effect.
Financial planners helped preserve and increase household net financial assets during the Great Recession.
In this article we present an alternative model for the distribution of household incomes in the United States. We provide arguments from two differing perspectives which both yield the proposed income distribution curve, and then fit this curve to empirical data on household income distribution obtained from the Unite…
We describe a method to identify poor households in data-scarce countries by leveraging information contained in nationally representative household surveys. It employs standard statistical learning techniques---cross-validation and parameter regularization---which together reduce the extent to which the model is over-…
This paper considers an optimal life insurance for a householder subject to mortality risk. The household receives a wage income continuously, which is terminated by unexpected (premature) loss of earning power or (planned and intended) retirement, whichever happens first. In order to hedge the risk of losing income st…
The 1/3 Financial Rule helps prevent household bankruptcy through balanced spending, savings, and debt repayment.
Model analyzes mortgage relief during financial hardship.
Develops a two-layer model to design mortgage assistance products.
A database of objects discovered in houses in the Roman city of Pompeii provides a unique view of ordinary life in an ancient city. Experts have used this collection to study the structure of Roman households, exploring the distribution and variability of tasks in architectural spaces, but such approaches are necessari…
Study analyzes household capital risk and poverty trapping, deriving a new function for capital deficit distribution.
Enhanced deep learning model forecasts household leverage series accurately.
We found a unified formula for description of the household incomes of all society classes, for instance, of those of the European Union in year 2007. This formula is a stationary solution of the threshold Fokker-Planck equation (derived from the threshold nonlinear Langevin one). The formula is more general than the w…
Study on stock portfolio concentration among Finnish households and investors.
Model shows how confidence feedback can lead to different crisis outcomes.
New method for disaggregate electricity demand forecasting at household level.
Intra-household inequality continues to remain a neglected corner despite renewed focus on income and wealth inequality. Using the LIS micro data, we present evidence that this neglect is equivalent to ignoring up to a third of total inequality. For a wide range of countries and over four decades, we show that at least…
Examines how extending home loan durations affects French households financially.
We found a unified formula for description of the household incomes of all society classes, for instance, for the European Union in years 2005-2010. The formula is more general than well known that of Yakovenko et al. because, it satisfactorily describes not only the household incomes of low- and medium-income society …
We study the forecasting of the power consumptions of a population of households and of subpopulations thereof. These subpopulations are built according to location, to exogenous information and/or to profiles we determined from historical households consumption time series. Thus, we aim to forecast the electricity con…
New measure predicts Dutch housing market downturns.
Study optimal portfolio for households with two goals: random and fixed deadlines.
We investigate the distribution function and the cumulative probability for Korean household incomes, i.e., the current, labor, and property incomes. For our case, the distribution functions are consistent with a power law. It is also showed that the probability density of income growth rates almost has the form of a e…
News on inflation and monetary policy impacts US household inflation expectations.
We investigate a multi-household DSGE model in which past aggregate consumption impacts the confidence, and therefore consumption propensity, of individual households. We find that such a minimal setup is extremely rich, and leads to a variety of realistic output dynamics: high output with no crises; high output with i…
We determine the optimal amount of life insurance for a household of two wage earners. We consider the simple case of exponential utility, thereby removing wealth as a factor in buying life insurance, while retaining the relationship among life insurance, income, and the probability of dying and thus losing that income…
This paper reports on our analysis of the 2011 CAMRa Challenge dataset (Track 2) for context-aware movie recommendation systems. The train dataset comprises 4,536,891 ratings provided by 171,670 users on 23,974$ movies, as well as the household groupings of a subset of the users. The test dataset comprises 5,450 rating…
Smart grid uses deep learning to optimize household energy use.
Subsidized insurance reduces poverty by providing social benefits and lowering government costs.
Recent studies using data on social media and stock markets have mainly focused on predicting stock returns. Instead of predicting stock price movements, we examine the relation between Facebook data and investors' decision making in stock markets with a unique data on investors' transactions on Nokia. We find that the…
Model explains capital allocation and wealth distribution dynamics in a frictional economy.
In order to improve the efficiency and sustainability of electricity systems, most countries worldwide are deploying advanced metering infrastructures, and in particular household smart meters, in the residential sector. This technology is able to record electricity load time series at a very high frequency rates, info…
I sketch a program for a microeconomic theory of the main component of the business cycle as a recurring disequilibrium, driven by incompleteness of the financial market and by information asymmetries between borrowers and lenders. This proposal seeks to incorporate five distinct but connected processes that have been …
Homeownership boosts wealth and welfare compared to renting, according to new research.
One shirt size cannot fit everybody, while we cannot make a unique shirt that fits perfectly for everyone because of resource limitation. This analogy is true for the policy making. Policy makers cannot establish a single policy to solve all problems for all regions because each region has its own unique issue. In the …
Variational auto-encoders (VAE) are scalable and powerful generative models. However, the choice of the variational posterior determines tractability and flexibility of the VAE. Commonly, latent variables are modeled using the normal distribution with a diagonal covariance matrix. This results in computational efficien…
As a type of pseudoinverse learning, extreme learning machine (ELM) is able to achieve high performances in a rapid pace on benchmark datasets. However, when it is applied to real life large data, decline related to low-convergence of singular value decomposition (SVD) method occurs. Our study aims to resolve this issu…
We report on results concerning a partially aggregated Stock Flow Consistent (SFC) macroeconomic model in the stationary state where the sectors of banks and firms are aggregated, the sector of households is dis-aggregated, and the probability density function (pdf) of the wealth of households is exogenous, constrained…
Fuel poverty affects between 50 and 125 million households in Europe and is a significant issue for both developed and developing countries globally. This means that fuel poor residents are unable to adequately warm their home and run the necessary energy services needed for lighting, cooking, hot water, and electrical…
The accuracy of the household electricity consumption forecast is vital in taking better cost effective and energy efficient decisions. In order to design accurate, proper and efficient forecasting model, characteristics of the series have to been analyzed. The source of time series data comes from Online Enerjisa Syst…
NPE trains neural networks to approximate posterior distributions in SIR models from final outcome data.